#computational-social-science News & Analysis

5 articles tagged with #computational-social-science. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

5 articles

AIBullisharXiv – CS AI · Mar 57/10

🧠

Bridging Computational Social Science and Deep Learning: Cultural Dissemination-Inspired Graph Neural Networks

Researchers introduce AxelGNN, a new Graph Neural Network architecture inspired by cultural dissemination theory that addresses key limitations of existing GNNs including oversmoothing and poor handling of heterogeneous relationships. The model demonstrates superior performance in node classification and influence estimation while maintaining computational efficiency across both homophilic and heterophilic graphs.

AINeutralarXiv – CS AI · Mar 116/10

🧠

Debiasing International Attitudes: LLM Agents for Simulating US-China Perception Changes

Researchers developed an LLM-agent framework to model how media influences US-China attitudes from 2005-2025, testing three debiasing mechanisms to reduce AI model prejudices. The study found that devil's advocate agents were most effective at producing human-like opinion formation, while revealing geographic biases tied to AI models' origins.

🧠 GPT-4

AINeutralarXiv – CS AI · Mar 35/104

🧠

German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies

Researchers have created GGSS Personas, a comprehensive collection of survey-derived persona prompts based on the German General Social Survey that helps Large Language Models simulate human perspectives more accurately. The collection enables LLMs to generate responses aligned with the German population and outperforms existing classifiers, particularly when training data is limited.

AINeutralarXiv – CS AI · Mar 44/102

🧠

A Natural Language Agentic Approach to Study Affective Polarization

Researchers developed a multi-agent platform using large language models to study affective polarization in social media through virtual communities. The framework addresses limitations of real-world studies by creating simulated environments where AI agents engage in discussions to analyze political and social divisions.

AINeutralarXiv – CS AI · Mar 25/107

🧠

Integrating LLM in Agent-Based Social Simulation: Opportunities and Challenges

A research position paper examines the integration of Large Language Models (LLMs) in agent-based social simulations, highlighting both opportunities and limitations. The study proposes Hybrid Constitutional Architectures that combine classical agent-based models with small language models and LLMs to balance expressive flexibility with analytical transparency.